Explainable AI and Mass Surveillance System-Based Healthcare Framework to Combat COVID-I9 Like Pandemics

From local explanations to global understanding with explainable AI for trees

Lundberg, S. M., Erion, G., Chen, H., DeGrave, A., Prutkin, J. M., Nair, B., Katz, R., Himmelfarb, J., Bansal, N., & Lee, S.-I. (2020) · Nature Machine Intelligence · doi:10.1038/s42256-019-0138-9 · Cited by 10,551

A Comprehensive Review of the COVID-19 Pandemic and the Role of IoT, Drones, AI, Blockchain, and 5G in Managing its Impact

Chamola, V., Hassija, V., Gupta, V., & Guizani, M. (2020) · IEEE Access · doi:10.1109/access.2020.2992341 · Cited by 1,099

5G-based smart healthcare network: architecture, taxonomy, challenges and future research directions

Ahad, A., Tahir, M., & Yau, K.-L. A. (2019) · IEEE Access · doi:10.1109/access.2019.2930628 · Cited by 352

Review of blockchain-based distributed energy: Implications for institutional development

Ahl, A., Yarime, M., Tanaka, K., & Sagawa, D. (2019) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2019.03.002 · Cited by 304

Secure UAV Communication Networks over 5G

Li, B., Fei, Z., Zhang, Y., & Guizani, M. (2019) · IEEE Wireless Communications · doi:10.1109/mwc.2019.1800458 · Cited by 202

Edge Intelligence in the Cognitive Internet of Things: Improving Sensitivity and Interactivity

Zhang⋆, Y., Ma, X., Zhang, J., Hossain, M. S., Muhammad, G., & Amin, S. U. (2019) · IEEE Network · doi:10.1109/mnet.2019.1800344 · Cited by 149

Future of Ultra-Dense Networks Beyond 5G: Harnessing Heterogeneous Moving Cells

Andreev, S. D., Петров, В. И., Döhler, M., & Yanıkömeroğlu, H. (2019) · IEEE Communications Magazine · doi:10.1109/mcom.2019.1800056 · Cited by 126

B5G and Explainable Deep Learning Assisted Healthcare Vertical at the Edge: COVID-I9 Perspective

Rahman, M. A., Hossain, M. S., Alrajeh, N. A., & Guizani, N. (2020) · IEEE Network · doi:10.1109/mnet.011.2000353 · Cited by 115

Emotion recognition using secure edge and cloud computing

Hossain, M. S., & Muhammad, G. (2019) · Information Sciences · doi:10.1016/j.ins.2019.07.040 · Cited by 104

An Automatic Health Monitoring System for Patients Suffering From Voice Complications in Smart Cities

Ali, Z., Muhammad, G., & Alhamid, M. F. (2017) · IEEE Access · doi:10.1109/access.2017.2680467 · Cited by 90

An Intelligent System for Video-Based Proximity Analysis

Antonov, S. V., Bogachev, M. I., Leyba, P., Sinitca, A., & Kaplun, D. (2023) · Studies in big data · doi:10.1007/978-981-99-3784-4_5 · Cited by 1

Analyzing the Application of Edge Computing in Smart Healthcare

Verma, P., & Kumar, U. (2023) · doi:10.1002/9781119905233.ch7 · Cited by 1

DeClEx-Processing Pipeline for Critical Healthcare ApplicationPreprint

Shinde, G., Goniguntla, S. C., Shirur, P., & Hambaba, A. (2024) · Preprints.org · doi:10.20944/preprints202405.0947.v1

Preventing and Controlling Epidemics through Blockchain-Assisted AI-Enabled NetworksPreprint

Otoum, S., Ridhawi, I. A., & Mouftah, H. T. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2104.13224

The Temperature Screening and Face Mask Detection for Preventing Spread of COVID-19

Kale, G., Jasoriya, A., Jain, D., & Narote, S. P. (2021) · International Journal of Advanced Research in Science Communication and Technology · doi:10.48175/ijarsct-1678

Applying Intelligent Reflector Surfaces for Detecting Respiratory Aerosol Cloud using Terahertz SignalsPreprint

Šiljak, H., Barros, M. T., D’Arcy, N., Martins, D. P., Marchetti, N., & Balasubramaniam, S. (2021) · arXiv (Cornell University)

How to Predict the Spread of COVID-19Preprint

Dadyan, E. G. (2021) · Research Square · doi:10.21203/rs.3.rs-941929/v1

Mapping Invisible Surveillance on the North Avenue Smart Corridor, Atlanta

Dortdivanlioglu, H. (2021) · Catalyst Feminism Theory Technoscience · doi:10.28968/cftt.v7i2.36687

Artificially Intelligent, Automatic, Modular Health Check Door to Ensure Safety against Covid - 19 and Other Epidemics

Chaudhary, A., Naithani, P., Gururani, M., & Rana, A. (2021) · International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) · doi:10.1109/icrito51393.2021.9596363

The Power of Computational Intelligence Methods in the Containment of COVID-19 Pandemic from Detection to Recovery

Isa, A., & Ndahi, B. P. (2021) · IntechOpen eBooks · doi:10.5772/intechopen.98931

Edge Computing to Solve Security Issues for Infectious Disease Intelligence Prevention

Lv, Z., Lou, R., & Lv, H. (2021) · ACM Transactions on Internet Technology · doi:10.1145/3475869

Delay-Sensitive Wireless Content Delivery: An Interpretable Artificial Intelligence Approach

Coronado, E., Gómez, B., Villalon, J. M., Garrido, A., Siddiqui, S., & Riggio, R. (2021) · International Conference on Network and Service Management (CNSM) · doi:10.23919/cnsm52442.2021.9615533

Post COVID-19 Intelligent Public Healthcare Management

Bristy, A. T., Ferdousi, R., Hossain, A., Islam, M. M. F., Hossain, M. A., & Saddik, A. E. (2021) · IEEE Globecom Workshops (GC Wkshps) · doi:10.1109/gcwkshps52748.2021.9682056

Proceedings of the Sixth International Conference on Research in Intelligent and Computing

(2022) · Annals of Computer Science and Information Systems · doi:10.15439/978-83-962423-2-7

iTrace: When IOTA Meets COVID-19 Contact Tracing

Ghazanfer, W., Minhas, N. N., Rauf, M., & Anjum, A. (2022) · IT Professional · doi:10.1109/mitp.2021.3134896

Interpreting Chest X-rays for COVID-19 Applying AI and Deep Learning: A Technical Review

Sugirtham, A. V. N., & Malathy, C. (2022) · Advances in intelligent systems and computing · doi:10.1007/978-981-16-5652-1_21

Best Practices on Advanced Condition Monitoring of Rail Infrastructure Systems

(2022) · Frontiers research topics · doi:10.3389/978-2-88971-914-3

Emerging Cyber Security Threats During the COVID-19 Pandemic and Possible Countermeasures

Suthar, H. (2022) · Advances in information security, privacy, and ethics book series · doi:10.4018/978-1-6684-5250-9.ch016

Adaptive Fuzzy Neural Network vs. Convolution Neural Network in Classifying COVID-19 from Chest X-rays

Alrashoud, M. R., & Rahman, M. A. (2022) · IEEE Globecom Workshops (GC Wkshps) · doi:10.1109/gcwkshps56602.2022.10008683

The Role of Edge Computing in Pandemic and Epidemic Situations with Its Solutions

Balamurugan, A. G., Pushpakumar, R., Selvakumari, S., & Kumar, S. P. (2023) · Signals and communication technology · doi:10.1007/978-3-031-19752-9_12

Marvelous Machine-Learning-Based Breast Cancer Predictive ModelPreprint

Anthoniraj, S., Saravanakumar, S., ANANDRAJ, M., & Anjaiah, P. (2023) · Research Square · doi:10.21203/rs.3.rs-3325357/v1

Analysing Breast Cancer using Convolution Neural Network

Kumari, S., & Rani, K. U. (2023) · International Journal of Membrane Science and Technology · doi:10.15379/ijmst.v10i2.2775

SDN-Based Network Resource Management

Silva, J., Moura, J., & Souto, N. M. B. (2023) · Disruptive technologies and digital transformations for society 5.0 · doi:10.1007/978-981-99-5354-7_8

OPTIMIZED ACCESS-CONTROL FRAMEWORK FOR REVITALIZING THE SECURITY OF PATIENT-CENTRIC ELECTRONIC HEALTH RECORDS

Rahi, P., Bandil, D. K., Shiwani, S., Soni, P., & Saxena, V. (2023) · Journal of Research Administration · doi:10.53555/jra.v5.i2.513

Hospital Medical Behaviour Supervision and Operational Efficiency Evaluation Method based based on Big Data Platform

Liu, Y., & Zhang, Y. (2024) · Scalable Computing Practice and Experience · doi:10.12694/scpe.v25i3.2764

Ocmael: An Optimal Corresponding Multimodal Adaptive Ensemble Learning Model for Brain Tumor SegmentationPreprint

Xu, J. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4822240

A Detailed Review on Challenges in the Computational Frameworks in Building 6G for Healthcare System

Shalini, M., Sharma, R., Bhuvaneswari, M., Badhoutiya, A., Mohan, M. M., & Rao, S. P. V. S. (2024) · International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) · doi:10.1109/icacite60783.2024.10617123

TWISH: an enhanced activation function for optimizing mental health and comorbidity risk assessment during COVID-19 using deep learning

Usharani, B. (2025) · Multimedia Tools and Applications · doi:10.1007/s11042-025-20685-6

Interpretable and Adaptive Security Mechanism for Next-Gen Industrial Networks

Lalitha, V., Reddy, A. D., Spandana, R. R. S., & Kumar, T. A. (2025) · International Journal of Applied Engineering and Management Letters · doi:10.47992/ijaeml.2581.7000.0236

Blockchain-Enabled Federated Learning for Collaborative Autonomous Vehicle Navigation

Ullah, F., Chowdhury, M. T. A., Alhussain, H., Kamal, S., & Bhushan, S. (2025) · International Conference on Metaverse and Current Trends in Computing (ICMCTC) · doi:10.1109/icmctc62214.2025.11196228

Secure Sharing of Medical Imaging Through Blockchain

Jain, P. A. (2025) · Scientific Journal of Artificial Intelligence and Blockchain Technologies · doi:10.63345/sjaibt.v2.i2.203

A Federated Intrusion Detection Framework for IoT Using Visual Encoding and Lightweight Secure Aggregation

Mabrouk, K. A., Metwally, K., Sobh, M., & Bahaa-Eldin, A. M. (2025) · Novel Intelligent and Leading Emerging Sciences Conference (NILES) · doi:10.1109/niles68063.2025.11232282

Explainable Artificial Intelligence (XAI) for Distributed Systems: A Survey

Saleem, R., Akram, N., Rajput, M. A., & Mahmood, I. (2025) · International Journal of Innovative Research in Computer Science & Technology · doi:10.55524/ijircst.2025.13.6.2

39Chapter 3 A systematic review of smart healthcare equity using IoT and augmented/virtual reality

Anbuselvi, D., GraceInfantiya, S., & Vanitha, N. S. (2025) · De Gruyter eBooks · doi:10.1515/9783111388588-003

Prominence of technological interventions in healthcare quality and hyper-personalisation: Unravelling the criticality of A.I., IoT & IoMT

Senapati, S., Panda, R. K., & Mishra, D. N. (2026) · Journal of Evolutionary Studies in Business-JESB · doi:10.1344/jesb.42939

Machine Learning-Driven Early Warning System for Epidemic and Pandemic Outbreaks with Explainable AI

Ahmed, R., Aurnima, S.-E.-A., Pranto, M. A. M., Tamanna, R., & Hossain, A. B. M. K. (2025) · IEEE International Conference on Computing, Applications and Systems (COMPAS) · doi:10.1109/compas67506.2025.11381739

Machine Learning Technique for Managing Vulnerable People During the Covid-19 and Related Pandemic Through Telemedicine: Systematic Review, Open Challenges, and Research Directions

Shuib, L. M., Eke, C. I., Azmi, N., Balakrishnan, V., & Rasak, H. A. (2026) · Neural Processing Letters · doi:10.1007/s11063-025-11807-0

Revolutionizing Healthcare for Critical Diseases with AI and Enhancing Security via Low-Latency Edge Intelligence

Islam, M. Z., Ahmed, I., Parveen, R., Rimon, S. M. T. H., & Janjua, J. I. (2025) · International Conference on AI-Driven STEM Education and Learning Technologies (AISTEMEDU) · doi:10.1109/aistemedu67077.2025.11403932

An Interpretable AutoML Framework for Detecting Payload Driven MQTT Flooding Attacks in Healthcare 5.0 IoMT Systems

Mohan Raj, D., & Jim Solomon Raja, D. (2026) · International Conference on Computing, Electronics & Communications Engineering (iCCECE) · doi:10.1109/iccece69715.2026.11492888

Intelligent Threat Hunting and Behavior-Based Malware Detection

Tripathi, A., Upadhyay, P., & Tyagi, S. (2026) · IGI Global eBooks · doi:10.4018/979-8-2600-1498-1.ch009

Contrastive Self-Supervised Learning for Network-Based Intrusion Detection in IoT Environments

Kumar, C. S. S., Sathyanarayanan, D., Potha, U., Shahid, S., Charitha, M. B., & Reddy, A. J. M. (2026) · International Conference on Intelligent Computing and Control Systems (ICICCS) · doi:10.1109/iciccs67901.2026.11503004

A trustworthy healthcare framework for secure disease detection using enhanced homomorphic encryption and explainable artificial intelligence models

Jain, R., Rani, A., & Gupta, P. (2026) · Network Modeling Analysis in Health Informatics and Bioinformatics · doi:10.1007/s13721-026-00773-9

Semantic-Aware Machine Learning with Ontology-Based Interoperability and XAI for Educational Data Integration and Interpretation

Thapa, D. M., & Shakya, S. (2026) · Procedia Computer Science · doi:10.1016/j.procs.2026.06.205

An Explainable Auto ML Framework for Detecting MQTT CONNECT Flooding Attacks in Healthcare 5.0 IoMT Systems

Mohan Raj, D., & Jim Solomon Raja, D. (2026) · International Conference on Innovations in Communication, Geoscience and Robotics (ICICGR) · doi:10.1109/icicgr68236.2026.11600081

Data-driven smart freight fleet management amid epidemic disruptions: A framework and case study

Paternina-Arboleda, C. D., Ramirez-Ríos, D. G., Zaballa, K., & Montoya‐Torres, J. R. (2026) · Health Care Management Science · doi:10.1007/s10729-026-09779-1

A privacy preserving and trustworthy hybrid deep learning model for zero-day DDoS detection in healthcare industry 5.0

Ali, A., Khan, M. F., Azim, N., & Aadil, F. (2026) · Cluster Computing · doi:10.1007/s10586-026-06463-5

Multilingual Health Chatbot for Disease Awareness Using Cross-Lingual Transformer Models and Ensemble Classification

Prakash, A., Paruti, R. B., Abhimanyu, Shwetha, P. R., & Harish, S. (2026) · International Conference on Next-Gen Intelligent Computing and Applications (ICONICA) · doi:10.1109/iconica70605.2026.11736833

A Deep-Learning-Based Edge-Centric COVID-19-Like Pandemic Screening and Diagnosis System within a B5G Framework Using Blockchain

Muhammad, G., & Hossain, M. S. (2021) · IEEE Network · doi:10.1109/mnet.011.2000326 · Cited by 36

B5G and Explainable Deep Learning Assisted Healthcare Vertical at the Edge: COVID-I9 Perspective

Rahman, M. A., Hossain, M. S., Alrajeh, N. A., & Guizani, N. (2020) · IEEE Network · doi:10.1109/mnet.011.2000353 · Cited by 115

An Intelligent Edge-as-a-Service Framework to Combat COVID-19 Using Deep Learning Techniques

Hassan, M. M., Al-Rakhami, M. S., Alabrah, A. A., & AlQahtani, S. A. (2023) · Mathematics · doi:10.3390/math11051216 · Cited by 4

Preventing and Controlling Epidemics Through Blockchain-Assisted AI-Enabled Networks

Otoum, S., Ridhawi, I. A., & Mouftah, H. T. (2021) · IEEE Network · doi:10.1109/mnet.011.2000628 · Cited by 27

Research and Application of 5G Edge AI in Medical Industry

Tang, S., Huo, M., Du, Y., Huo, Y., Zhang, K., Xu, L., Ji, Y., & Zhou, G. (2022) · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) · doi:10.1109/trustcom56396.2022.00207 · Cited by 5